Trip chain complexity: a comparison among latent classes of daily mobility patterns

This paper studies the relationship between trip chain complexity and daily travel behaviour of travellers. While trip chain complexity is conventionally investigated between travel modes, our scope is the more aggregated level of a person’s activity-travel pattern. Using data from the Netherlands Mobility Panel, a latent class cluster analysis was performed to group people with similar mode choice behaviour in distinct mobility pattern classes. All trip chains were assigned to both a travel mode and the mobility pattern class of the traveller. Subsequently, differences in trip chain complexity distributions were analysed between travel modes and between mobility pattern classes. Results indicate considerable differences between travel modes, particularly between multimodal and unimodal trip chains, but also between the unimodal travel modes car, bicycle, walking and public transport trip chains. No substantial differences in trip chain complexity were found between mobility pattern classes. Independently of the included travel modes, the distributions of trip chain complexity degrees were similar across mobility pattern classes. This means that personal circumstances such as the number of working hours or household members are not systematically translated into specific mobility patterns.

     

Trip chaining as a barrier to the propensity to use public transport

Trip chaining is a growing phenomenon in travel and activity behaviour. Individuals increasingly seek out opportunities to minimise the amount of travel required as part of activity fulfilment, given the competing demands on time budgets and their valuation of travel time savings. This search for ways of fulfilling (more) activities with less travel input has produced a number of responses, one of which is trip chaining. A particularly important policy implication of trip chaining is the potential barrier it creates in attracting car users to switch to public transport. This paper seeks to improve our understanding of trip chaining as a barrier to public transport use. A series of discrete choice models are estimated to identify the role that socio-economic and demographic characteristics of households have on the propensity to undertake trip chains of varying degrees of simplicity/complexity that involve use of the car or public transport with an embedded commuting or non-commuting primary purpose. Multinomial logit, nested logit and random parameter logit models are developed and contrasted to establish the gains in relaxing the strict conditions of the multinomial logit model.     

Trip generation of vulnerable populations in three Canadian cities: a spatial ordered probit approach

This paper provides an analysis of trip generation of three vulnerable groups: single-parent families, low income households, and the elderly. It compares the mobility of these groups to that of the general population in three Canadian urban areas of Hamilton, Montreal and Toronto, based on data from large-sample metropolitan transport surveys. An ordered probit model with spatially expanded coefficients is used for the analysis. Spatial expansion shows that there are spatial mobility trends for elderly populations and low-income populations even after socio-economic attributes are accounted for. Such spatial differences are not generally found for single parent families. This novel spatial analysis provides clues as to where vulnerable populations may experience greater degrees of social exclusion. It provides information to help prioritize transportation infrastructure projects or other social programs to take into account the needs of vulnerable populations with the lowest levels of mobility.     

Modelling the relationship between travel behaviours and social disadvantage

The purpose of this paper is to model the travel behaviour of socially disadvantaged population segments in the United Kingdom (UK) using the data from the UK National Travel Survey 2002–2010. This was achieved by introducing additional socioeconomic variables into a standard national-level trip end model (TEM) and using purpose-based analysis of the travel behaviours of certain key socially disadvantaged groups. Specifically the paper aims to explore how far the economic and social disadvantages of these individuals can be used to explain the inequalities in their travel behaviours.The models demonstrated important differences in travel behaviours according to household income, presence of children in the household, possession of a driver’s licence and belonging to a vulnerable population group, such as being disabled, non-white or having single parent household status. In the case of household income, there was a non-linear relationship with trip frequency and a linear one with distance travelled. The recent economic austerity measures that have been introduced in the UK and many other European countries have led to major cutbacks in public subsidies for socially necessary transport services, making results such as these increasingly important for transport policy decision-making. The results indicate that the inclusion of additional socioeconomic variables is useful for identifying significant differences in the trip patterns and distances travelled by low-income.     

Mobility behavior of the elderly: an attitude-based segmentation approach for a heterogeneous target group

The western population is ageing. Based on the assumption that the elderly are a quite heterogeneous population group with an increasing impact on the transport system, mobility types of the elderly were identified. By means of 1,500 standardized telephone interviews, mobility behavior and possible determinantes including infrastructural, sociodemographic and attitudinal variables, were assessed. The most important factors, identified by five regression analyses, served as type-constituent variables in a series of cluster analyses. The final cluster solution resulted in four segments of the elderly named Captive Car Users, Affluent Mobiles, Self-Determined Mobiles, and Captive Public Transport Users. The groups showed distinct mobility patterns as well as significant differences in infrastructural, sociodemographic and attitudinal variables. The study provides a more comprehensive understanding of the diverse lifestyles, attitudes, travel behavior and needs of the elderly. Furthermore, it identifies starting points for the reduction of car use.     

The mobility and accessibility expectations of seniors in an aging population

Populations of post-industrial nations are aging. With a growing number of people living well into their 80s and maintaining active lives, the transportation system will have to start focussing more closely on understanding their mobility and accessibility needs, so as to ensure that specific requirements of this large segment are not being ignored through the promotion of traditional ‘solutions’ and historical assumptions. This paper takes a close look at the evidence on the mobility needs and travel patterns of individuals over 64, distinguishing between the “young” elderly (aged 65–75 years) and the “old” elderly (over 75 years). This distinction is particularly useful in recognising the threshold of health change that impacts in a non-marginal way on mobility needs. This distinction also focuses transport planning and policy on a commitment to understanding the different needs of these sub-groups of the population, identifying services and facilities that better cater for these groups. We review the evidence, in particular, on the mobility characteristics of the over 75 years age group, including how they secure support through migration and settlement patterns. We use the empirical evidence from a number of western nations to identify the role of conventional and specialised public transport as an alternative to the automobile in meeting mobility and accessibility needs.     

Gender differentials in travel pattern – The case of a mid-sized city,Rajkot, India

This paper is at the conjunction of arguments for gender equity in transport services on one hand and need to move towards low carbon transport on the other in a developing country city. The case study city, Rajkot, a mid-sized Indian city with mixed land use and limited public transport at the time of this study, has short trip lengths and low trip rates. But, even in this city there is gender disparity in travel pattern. Thus, trip rates and trip lengths of women in the city in each of the income group are lower than that of their male counter parts. With the increase in income, both, the trip rates and lengths increase, but, the increase is higher for men than for women. While the large proportions of women in each income group walk, that among the lowest income group walking is the predominant mode, as they are ‘no-choice’ or ‘forced’ walkers. With the increase in household income, women tend to shift to para-transit and men to personal motorized transport. If sustainability arguments or climate policies are to target retaining the current low ecological footprint of the women as one of the strategies, it needs to cater to expansion of their mobility while improving infrastructure to support the same.     

Modeling travel behavior by the structural relationships between lifestyle,built environment and non-working trips

In the context of sustainable urban transport in developing countries, individuals’ travel behavior faces multiple factors which influence their mobility patterns. Recognizing these factors could be a favorable method to organize more regular and sustainable trip patterns. This study aims to identify the less well-known lifestyle along with more popular built environment as the main factors which shape travel behaviors. Employing data from 900 respondents of 22 urban areas in city of Shiraz, Iran, this paper explores travel behaviors as non-working trip frequencies by different modes. Results of structural equation model indicate a strong significant effect of individual’s lifestyle patterns on their non-working trips. However, built environment impact on travel behavior is small compared to lifestyle. Besides, other variables such as travel attitudes and socio-economic factors stay crucial in the mode choice selection. These findings indicate the necessity of regarding lifestyle orientations in travel studies as well as objective factors such as land use attributes.     

Space and time related determinants of public transport use in trip chains

This research aims at gaining a better understanding about time and space related determinants, which are generally acknowledged to be important factors in the choice of transport mode. The effect of trip chaining is taken into account to improve the insight in the relation between the choice of transport mode and time factors. The data source is the first large scale Belgian mobility survey, carried out in 1998–1999, complemented with a newly created database, containing for each trip a calculated public transport trip. This allows comparing for each trip the actual travel time with the calculated travel time by public transport. Using elasticities and regression techniques the relation between travel time components and public transport use is quantified. On trip level, a clear relation is found between waiting and walking time and public transport use. On trip chain level, travel time variables for the whole trip chain such as the maximum and the range in the travel time ratio provide a significant improvement to the explanatory power of the regression model. The results contain parameters for model input and recommendations to public transport companies on information provision, intermodality and supply.     

Lifestyles and transportation needs of the elderly in Los Angeles

This study examined the trip-making behavior of persons over 65 years of age residing in Los Angeles County. To date, the major shortcoming of most research concerned with the transportation needs of the elderly is that the aged have been treated as a homogeneous group without recognizing the various lifestyles of the senior population. The two most easily distinguishable groups of elderly persons within the county are those residing in the inner-city and those around the urban fringe. Although many elderly are still found in gray ghettos there is currently a trend toward a more suburban generation of retirees. Four areas were selected within the county that reflected these two living patterns of the elderly. A comparative analysis of trip patterns and socio-economic data was completed. It was found that the suburban elderly are characterized as (1) having higher incomes, (2) residing predominantly in single-family units and (3) being reliant upon automobile transportation. As is typical of a large proportion of those over 65 years of age, many of the suburban elderly cannot drive. Studies of the transportation needs of this group indicate that without transit alternatives they may well become society's most transit-deprived segment. On the other hand, while the inner-city elderly may have a wider range of transportation options, they also have a distinct economic disadvantage which preludes their accessibility to opportunities. An analysis of modal choices, trip purposes and the frequency of travel exhibited many similarities and some significant differences in the travel behavior as well as problems of these two groups.In addition to investigating travel patterns a survey of taxi-cab use on weekends and weekdays was undertaken. Elderly persons represent a substantial proportion of taxi-cab patrons. Their use of taxis is further indicative of the change that occurs in mobility patterns upon reaching retirement. This mode of transportation is presently the only type of demand-responsive service available to the senior population in some parts of the county.This report was produced as part of a program of Research and Training in Urban Transportation sponsored by the Urban Mass Transportation Administration of the U.S. Department of Transportation. The results and views expressed are the independent products of university research and are not necessarily concurred in by the Urban Mass Transportation Administration of the Department of Transportation.     

Direct and indirect influences on employed adults’ travel in the UK: New insights from the National Travel Survey data 2002–2010

Recent years saw a continuing shift in labour force composition, e.g. greater participation of women and a prominent rise in part-time workers. There are as yet relatively few recent studies that examine systematically the influences on the travel of employed adults from such perspectives, particularly regarding possible transport disadvantages of the fastest growing segments of workers. A robust analysis requires systematic data on a wide range of explanatory variables and multiple travel outcomes including accessibility, mobility and trip frequency for different trip purposes. The UK NTS data does meet the majority of this demanding data requirement, but its full use has so far been hampered by methodological difficulties. To overcome complex endogeneity problems, we develop novel, integrated structural equation models (SEMs) to uncover the influences of latent land use characteristics, indirect influences on car ownership, interactions among trip purposes as well as residents’ self-selection and spatial sorting. This general-purpose method provides a new, systematic decomposition of the influences on travel outcomes, where the effects of each variable can be examined in turn with robust error terms. The new insights underline two direct policy implications. First, it highlights the contributions of land use planning and urban design in restraining travel demand in the 2000s, and their increasing influence over the decade. Secondly, it shows that there may still be a large mobility disadvantage among the fastest growing segments of workers, particularly in dense urban areas. This research further investigates trend breaking influences before and after 2007 through grouped SEM models, as a test of the methodology for producing regular and timely updates regarding the main influences on personal travel from a system level.     

An adaptive hawkes process formulation for estimating time-of-day zonal trip arrivals with location-based social networking check-in data

Location-Based Social Networking (LBSN) services, such as Foursquare, Facebook check-ins, and Geo-tagged Twitter tweets, have emerged as new secondary data sources for studying individual travel mobility patterns at a fine-grained level. However, the differences between human social behavioral and travel patterns can cause significant sampling bias for travel demand estimation. This paper presents a dynamic model to estimate time-of-day zonal trip arrival patterns. In the proposed model, the state propagation is formulated by the Hawkes process; the observation model implements LBSN sampling. The proposed model is applied to Foursquare check-in data collected from Austin, Texas in 2010 and calibrated with Origin-Destination (OD) data and time of day factor from Capital Area Metropolitan Planning Organization (CAMPO). The proposed model is compared with a simple aggregation model of trip purposes and time of day based on a prior daily OD estimation model using the LBSN data. The results illustrate the promising benefits of applying stochastic point process models and state-space modeling in time-of-day zonal arrival pattern estimation with the LBSN data. The proposed model can significantly reduce the number of parameters to calibrate in order to reduce the sampling bias of LBSN data for trip arrival estimation.     

Modelling car trip generations for UK residential developments using data from TRICS

Abstract

This paper models trip generation for a cross-section of residential developments around the UK. Consistent with recent literature, the empirical model tests whether trip making patterns for residential developments are independent of car ownership and finds that trip generation is dependent upon car ownership socio-economic factors and site-specific characteristics, in particular land-zone type (e.g. town centre, out of town, etc.). However, public transport services are not found to have a significant relationship with trip generation; consequently, a policy implication of the results is that increasing bus services to residential developments is not associated with a reduction in generated trips.     

Patterns of car usage and restraint modelling

Transport demand forecasting procedures have traditionally employed household based modal split models implicitly assuming a selection of mode for each trip based on relative generalised cost. A detailed examination of the trip patterns of a sample of household in West Yorkshire shows that in fact there is little discretionary choice of public transport; public transport trips in car owning households generally being explained in terms of the specific unavailability of the car for such trips. Two versions of a category analysis model for modal split are based on this observation and applied to household data for Glamorgan and Monmouthshire to show that such a procedure is workable and produces results comparing favourably with traditional approaches. The likely implications of three types of restraint policy are examined and it is concluded that the existing interdependence in trip patterns and modal choice within the household is of great significance in determining their effects. In particular it appears that positive attempts to increase vehicle occupancy at the peak are likely to be more favourable to public transport finances than the more negative policies to restrain use of the car for journey to work, or second car ownership.     

The Dublin transportation study

This article deals with the Transportation Study currently nearing completion in Dublin. A feature of this Study was the use of simplified data collection and modelling techniques. Beginning with a brief outline of the background to the transportation problem in Dublin, the article goes on to outline the objectives of the Study and the methods by which these objectives were fulfilled. These methods involved the taking of detailed inventories of Dublin's travel patterns, of its land uses, population and employment, and of its road and public transport systems. Mathematical models were then developed and modified until they could simulate the existing travel patterns to an acceptable degree of accuracy. These models covered the Study's trip generation, modal split, trip distribution and trip assignment stages, and the forms taken by the models are dealt with in the article. The article ends with a summary of the main recommendations of the Dublin Transportation Study.     

Exploring public transport usage trends in an ageing population

An ageing population remains one of the most significant challenges for Western society in the 21st century. Whilst public transport use has attractive sustainability features for older generations there is mixed evidence with regard to trends in travel and public transport use in ageing societies. This paper explores public transport trip rates amongst older age groups using travel survey evidence collected from a household travel survey in Melbourne, Australia for the period 1994 to 1999. A particular aim of the research was to establish trends in trip rates so as to explore the impact of the ageing Baby Boomer generation on travel by public transport. The results suggested that compared to those aged below 60, those aged over 60 years demonstrated 30% lower trip making overall and 16% lower public transport trip rates. Longitudinal trends in trip rates showed those aged over 60 had a very small decline in trip rates by public transport (−0.004 average daily trips per annum) but increasing rates for car trips. A further analysis showed a small but significant increase in longitudinal trip rates of public transport use amongst Baby Boomers (0.004 daily trips p.a., p < .05) while car usage for Baby Boomers was steady. The implication of these findings is that trends in the existing over 60s population are not necessarily going to flow through to behaviour patterns in the Baby Boomer generations. The Baby Boomer age group showed longitudinal trends in travel behaviour which contrasted with those of the existing over 60s generation notably with a trend towards increased public transport usage.     

Is accessibility relevant in trip generation? Modelling the interaction between trip generation and accessibility taking into account spatial effects

The influence of accessibility to opportunities in trip generation continues to be debated in the specialised literature given its relevance to simulate phenomena such as induced demand. This article estimates multiple linear regression models (MLR), spatial autoregressive models (SAR), spatial autoregressive models in the error term (SEM) and spatially filtered Poisson regression models (SPO) to discover whether or not accessibility is a significant factor in trip generation using data from the urban area of Santander (Spain). The results obtained provide evidence which shows that, on an intraurban scale, more accessibility to opportunities decreases trip production in private vehicle for work purpose, whereas it increases trip production in other transport modes for non—mandatory purposes. For the correct interpretation of the estimated parameters it was important to consider the direct and indirect effects of the independent variables in the SAR production models. Finally, the validation of the models showed that the SAR and SEM models had a mean squared error slightly lower than the MLR models in predicting overall trip production. This was because the spatial models reduced the correlation of the residuals present in the MLR models. Furthermore, the SPO models performed better in validation mode than all the continuous models.